In [27]:
%matplotlib inline

import pypolyagamma as pyp
import seaborn as sns
import numpy as np
import pandas as pd

sns.set()

In [28]:
pg_rng = pyp.PyPolyaGamma()

In [29]:
# this doesn't seem to work
a = np.repeat(2., 100)
pg_rng.pgdrawv(np.repeat(1., 100), np.repeat(0., 100), np.empty(100, dtype=np.float64))

In [30]:
pd.Series([pg_rng.pgdraw(1, 0) for i in range(100000)]).hist(bins=40, normed=True)


Out[30]:
<matplotlib.axes._subplots.AxesSubplot at 0x112dd5550>

In [31]:
pd.Series([pg_rng.pgdraw(1, 1) for i in range(100000)]).hist(bins=40, normed=True)


Out[31]:
<matplotlib.axes._subplots.AxesSubplot at 0x1155c79b0>

In [32]:
pd.Series([pg_rng.pgdraw(1, 10) for i in range(100000)]).hist(bins=40, normed=True)


Out[32]:
<matplotlib.axes._subplots.AxesSubplot at 0x115dfe748>

In [33]:
pd.Series([pg_rng.pgdraw(1, 100) for i in range(100000)]).hist(bins=40, normed=True)


Out[33]:
<matplotlib.axes._subplots.AxesSubplot at 0x11586beb8>

In [34]:
pd.Series([pg_rng.pgdraw(10, 0) for i in range(100000)]).hist(bins=40, normed=True)


Out[34]:
<matplotlib.axes._subplots.AxesSubplot at 0x115ecf8d0>

In [35]:
pd.Series([pg_rng.pgdraw(10, 1) for i in range(100000)]).hist(bins=40, normed=True)


Out[35]:
<matplotlib.axes._subplots.AxesSubplot at 0x1161a3518>

In [36]:
pd.Series([pg_rng.pgdraw(10, 10) for i in range(100000)]).hist(bins=40, normed=True)


Out[36]:
<matplotlib.axes._subplots.AxesSubplot at 0x1158a4b38>

In [37]:
pd.Series([pg_rng.pgdraw(10, 100) for i in range(100000)]).hist(bins=40, normed=True)


Out[37]:
<matplotlib.axes._subplots.AxesSubplot at 0x11663ee80>

In [38]:
pd.Series([pg_rng.pgdraw(100, 0) for i in range(100000)]).hist(bins=40, normed=True)


Out[38]:
<matplotlib.axes._subplots.AxesSubplot at 0x115fc6128>

In [39]:
pd.Series([pg_rng.pgdraw(100, 1) for i in range(100000)]).hist(bins=40, normed=True)


Out[39]:
<matplotlib.axes._subplots.AxesSubplot at 0x115fb8278>

In [40]:
pd.Series([pg_rng.pgdraw(100, 10) for i in range(100000)]).hist(bins=40, normed=True)


Out[40]:
<matplotlib.axes._subplots.AxesSubplot at 0x116d662b0>

In [41]:
pd.Series([pg_rng.pgdraw(100, 100) for i in range(100000)]).hist(bins=40, normed=True)


Out[41]:
<matplotlib.axes._subplots.AxesSubplot at 0x117afdc18>

In [ ]: